Translational Landscape of Protein-Coding and Non-Protein-Coding RNAs upon Light Exposure in Arabidopsis

2019 ◽  
Vol 61 (3) ◽  
pp. 536-545 ◽  
Author(s):  
Yukio Kurihara ◽  
Yuko Makita ◽  
Haruka Shimohira ◽  
Tomoya Fujita ◽  
Shintaro Iwasaki ◽  
...  
Keyword(s):  
Blue Light ◽  
Environmental Changes ◽  
De Novo ◽  
Light Exposure ◽  
Monochromatic Light ◽  
Ribosome Profiling ◽  
Open Reading Frames ◽  
Translation Efficiency ◽  
Protein Coding ◽  
Negative Effect

Abstract Light is one of the most essential environmental clues for plant growth and morphogenesis. Exposure to blue monochromatic light from darkness is a turning point for plant biological activity, and as a result dramatic changes in gene expression occur. To understand the translational impacts of blue light, we have performed ribosome profiling analysis and called translated open reading frames (ORFs) de novo within not only mRNAs but also non-coding RNAs (ncRNAs). Translation efficiency of 3,823 protein-coding ORFs, such as nuclear chloroplast-related genes, was up-regulated by blue light exposure. Moreover, the translational activation of the microRNA biogenesis-related genes, DCL1 and HYL1, was induced by blue light. Considering the 3-nucleotide codon periodicity of ribosome footprints, a few hundred short ORFs lying on ncRNAs and upstream ORFs (uORFs) on mRNAs were found that had differential translation status between blue light and dark. uORFs are known to have a negative effect on the expression of the main ORFs (mORFs) on the same mRNAs. Our analysis suggests that the translation of uORFs is likely to be more stimulated than that of the corresponding mORFs, and uORF-mediated translational repression of the mORFs in five genes was alleviated by blue light exposure. With data-based annotation of the ORFs, our analysis provides insights into the translatome in response to environmental changes, such as those involving light.

scholarly journals An Improved Human smORF Annnotation Workflow Combining De Novo Transcriptome Assembly and Ribo-Seq

2019 ◽  
Author(s):  
Thomas F. Martinez ◽  
Qian Chu ◽  
Cynthia Donaldson ◽  
Dan Tan ◽  
Maxim N. Shokhirev ◽  
...  
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Human Leukocyte ◽  
Open Reading Frames ◽  
Translation Efficiency ◽  
Proteomics Data ◽  
Protein Coding ◽  
Leukocyte Antigen ◽  
Human Genes ◽  
Small Open Reading Frames

Protein-coding small open reading frames (smORFs) are emerging as an important class of genes, however, the coding capacity of smORFs in the human genome is unclear. By integrating de novo transcriptome assembly and Ribo-Seq, we confidently annotate thousands of novel translated smORFs in three human cell lines. We find that smORF translation prediction is noisier than for annotated coding sequences, underscoring the importance of analyzing multiple experiments and footprinting conditions. These smORFs are located within non-coding and antisense transcripts, the UTRs of mRNAs, and unannotated transcripts. Analysis of RNA levels and translation efficiency during cellular stress identifies regulated smORFs, providing an approach to select smORFs for further investigation. Sequence conservation and signatures of positive selection indicate that encoded microproteins are likely functional. Additionally, proteomics data from enriched human leukocyte antigen complexes validates the translation of hundreds of smORFs and positions them as a source of novel antigens. Thus, smORFs represent a significant number of important, yet unexplored human genes.

scholarly journals A spectral analysis approach to detect actively translated open reading frames in high-resolution ribosome profiling data

2015 ◽  
Author(s):  
Lorenzo Calviello ◽  
Neelanjan Mukherjee ◽  
Emanuel Wyler ◽  
Henrik Zauber ◽  
Antje Hirsekorn ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Gene Expression Regulation ◽  
De Novo ◽  
Ribosome Profiling ◽  
Open Reading Frames ◽  
Mass Spectrometry Data ◽  
Hek293 Cells ◽  
Protein Coding ◽  
Reading Frame ◽  
Reading Frames

RNA sequencing protocols allow for quantifying gene expression regulation at each individual step, from transcription to protein synthesis. Ribosome Profiling (Ribo-seq) maps the positions of translating ribosomes over the entire transcriptome. Despite its great potential, a rigorous statistical approach to identify translated regions by means of the characteristic three-nucleotide periodicity of Ribo-seq data is not yet available. To fill this gap, we developed RiboTaper, which quantifies the significance of periodic Ribo-seq reads via spectral analysis methods. We applied RiboTaper on newly generated, deep Ribo-seq data in HEK293 cells, to derive an extensive map of translation that covers Open Reading Frame (ORF) annotations for more than 11,000 protein- coding genes. We also find distinct ribosomal signatures for several hundred detected upstream ORFs and ORFs in annotated non-coding genes (ncORFs). Mass spectrometry data confirms that RiboTaper achieves excellent coverage of the cellular proteome and validates dozens of novel peptide products. Collectively, RiboTaper (available at https://ohlerlab.mdc-berlin.de/software/ ) is a powerful method for comprehensive de novo identification of actively used ORFs in the human genome.

scholarly journals Disrupting upstream translation in mRNAs is associated with human disease

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
David S. M. Lee ◽  
Joseph Park ◽  
Andrew Kromer ◽  
Aris Baras ◽  
Daniel J. Rader ◽  
...  
Keyword(s):  
Protein Expression ◽  
Biological Significance ◽  
Ribosome Profiling ◽  
Open Reading Frames ◽  
Protein Coding ◽  
Stop Codons ◽  
Human Genes ◽  
Strong Negative Selection ◽  
Disease Associations ◽  
Reading Frames

AbstractRibosome-profiling has uncovered pervasive translation in non-canonical open reading frames, however the biological significance of this phenomenon remains unclear. Using genetic variation from 71,702 human genomes, we assess patterns of selection in translated upstream open reading frames (uORFs) in 5’UTRs. We show that uORF variants introducing new stop codons, or strengthening existing stop codons, are under strong negative selection comparable to protein-coding missense variants. Using these variants, we map and validate gene-disease associations in two independent biobanks containing exome sequencing from 10,900 and 32,268 individuals, respectively, and elucidate their impact on protein expression in human cells. Our results suggest translation disrupting mechanisms relating uORF variation to reduced protein expression, and demonstrate that translation at uORFs is genetically constrained in 50% of human genes.

scholarly journals RiboToolkit: an integrated platform for analysis and annotation of ribosome profiling data to decode mRNA translation at codon resolution

2020 ◽  
Vol 48 (W1) ◽  
pp. W218-W229 ◽  
Author(s):  
Qi Liu ◽  
Tanya Shvarts ◽  
Piotr Sliz ◽  
Richard I Gregory
Keyword(s):  
Mrna Translation ◽  
Ribosome Profiling ◽  
Open Reading Frames ◽  
Translational Efficiency ◽  
Translation Efficiency ◽  
Sequencing Data ◽  
Experimental Conditions ◽  
Web Based ◽  
Rna Translation ◽  
Web Interfaces

Abstract Ribosome profiling (Ribo-seq) is a powerful technology for globally monitoring RNA translation; ranging from codon occupancy profiling, identification of actively translated open reading frames (ORFs), to the quantification of translational efficiency under various physiological or experimental conditions. However, analyzing and decoding translation information from Ribo-seq data is not trivial. Although there are many existing tools to analyze Ribo-seq data, most of these tools are designed for specific or limited functionalities and an easy-to-use integrated tool to analyze Ribo-seq data is lacking. Fortunately, the small size (26–34 nt) of ribosome protected fragments (RPFs) in Ribo-seq and the relatively small amount of sequencing data greatly facilitates the development of such a web platform, which is easy to manipulate for users with or without bioinformatic expertise. Thus, we developed RiboToolkit (http://rnabioinfor.tch.harvard.edu/RiboToolkit), a convenient, freely available, web-based service to centralize Ribo-seq data analyses, including data cleaning and quality evaluation, expression analysis based on RPFs, codon occupancy, translation efficiency analysis, differential translation analysis, functional annotation, translation metagene analysis, and identification of actively translated ORFs. Besides, easy-to-use web interfaces were developed to facilitate data analysis and intuitively visualize results. Thus, RiboToolkit will greatly facilitate the study of mRNA translation based on ribosome profiling.

scholarly journals Genome-wide identification of Arabidopsis non-AUG-initiated upstream ORFs with evolutionarily conserved regulatory sequences that control protein expression levels

2021 ◽  
Author(s):  
Yuta Hiragori ◽  
Hiro Takahashi ◽  
Noriya Hayashi ◽  
Shun Sasaki ◽  
Kodai Nakao ◽  
...  
Keyword(s):  
Regulatory Peptides ◽  
Inhibitory Effect ◽  
Ribosome Profiling ◽  
Open Reading Frames ◽  
Regulatory Sequences ◽  
Dependent Manner ◽  
Protein Coding ◽  
Genome Wide ◽  
Evolutionarily Conserved ◽  
Upstream Open Reading Frames

Upstream open reading frames (uORFs) are short ORFs found in the 5′-UTRs of many eukaryotic transcripts and can influence the translation of protein-coding main ORFs (mORFs). Recent genome-wide ribosome profiling studies have revealed that thousands of uORFs initiate translation at non-AUG start codons. However, the physiological significance of these non-AUG uORFs has so far been demonstrated for only a few of them. It is conceivable that physiologically important non-AUG uORFs are evolutionarily conserved across species. In this study, using a combination of bioinformatics and experimental approaches, we searched the Arabidopsis genome for non-AUG-initiated uORFs with conserved sequences that control the expression of the mORF-encoded proteins. As a result, we identified four novel regulatory non-AUG uORFs. Among these, two exerted repressive effects on mORF expression in an amino acid sequence-dependent manner. These two non-AUG uORFs are likely to encode regulatory peptides that cause ribosome stalling, thereby enhancing their repressive effects. In contrast, one of the identified regulatory non-AUG uORFs promoted mORF expression by alleviating the inhibitory effect of a downstream AUG-initiated uORF. These findings provide insights into the mechanisms that enable non-AUG uORFs to play regulatory roles despite their low translation initiation efficiencies.

scholarly journals A de novo evolved gene in the house mouse regulates female pregnancy cycles

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Chen Xie ◽  
Cemalettin Bekpen ◽  
Sven Künzel ◽  
Maryam Keshavarz ◽  
Rebecca Krebs-Wheaton ◽  
...  
Keyword(s):  
House Mouse ◽  
De Novo ◽  
Specific Protein ◽  
Ribosome Profiling ◽  
Mass Spectrometry Data ◽  
Preimplantation Embryos ◽  
Protein Coding ◽  
Reading Frame ◽  
Protein Coding Genes ◽  
New Genes

The de novo emergence of new genes has been well documented through genomic analyses. However, a functional analysis, especially of very young protein-coding genes, is still largely lacking. Here, we identify a set of house mouse-specific protein-coding genes and assess their translation by ribosome profiling and mass spectrometry data. We functionally analyze one of them, Gm13030, which is specifically expressed in females in the oviduct. The interruption of the reading frame affects the transcriptional network in the oviducts at a specific stage of the estrous cycle. This includes the upregulation of Dcpp genes, which are known to stimulate the growth of preimplantation embryos. As a consequence, knockout females have their second litters after shorter times and have a higher infanticide rate. Given that Gm13030 shows no signs of positive selection, our findings support the hypothesis that a de novo evolved gene can directly adopt a function without much sequence adaptation.

scholarly journals Evidence for functional and non-functional classes of peptides translated from long non-coding RNAs

2016 ◽  
Author(s):  
Jorge Ruiz-Orera ◽  
Pol Verdaguer-Grau ◽  
José Luis Villanueva-Cañas ◽  
Xavier Messeguer ◽  
M Mar Albà
Keyword(s):  
De Novo ◽  
Gene Evolution ◽  
Ribosome Profiling ◽  
Open Reading Frames ◽  
Polymorphism Analysis ◽  
Proteomics Data ◽  
Functional Protein ◽  
Codon Composition ◽  
Functional Classes ◽  
Chance Occurrence

AbstractThere is accumulating evidence that some genes have originated de novo from previously non-coding genomic sequences. However, the processes underlying de novo gene birth are still enigmatic. In particular, the appearance of a new functional protein seems highly improbable unless there is already a pool of neutrally evolving peptides that can at some point acquire new functions. Here we show for the first time that such peptides do not only exist but that they are prevalent among the translation products of mouse genes that lack homologues in rat and human. The data suggests that the translation of these peptides is due to the chance occurrence of open reading frames with a favorable codon composition. Our approach combines ribosome profiling experiments, proteomics data and non-synonymous and synonymous nucleotide polymorphism analysis. We propose that effectively neutral processes involving the expression of thousands of transcripts all the way down to proteins provide a basis for de novo gene evolution.

scholarly journals uORF-Tools – Workflow for the determination of translation-regulatory upstream open reading frames

2018 ◽  
Author(s):  
Anica Scholz ◽  
Florian Eggenhofer ◽  
Rick Gelhausen ◽  
Björn Grüning ◽  
Kathi Zarnack ◽  
...  
Keyword(s):  
Ribosome Profiling ◽  
Open Reading Frames ◽  
Annotation File ◽  
Inhibitory Effects ◽  
Protein Coding ◽  
Reading Frame ◽  
Upstream Open Reading Frames ◽  
Induced Changes ◽  
Reading Frames

AbstractRibosome profiling (ribo-seq) provides a means to analyze active translation by determining ribosome occupancy in a transcriptome-wide manner. The vast majority of ribosome protected fragments (RPFs) resides within the protein-coding sequence of mRNAs. However, commonly reads are also found within the transcript leader sequence (TLS) (aka 5’ untranslated region) preceding the main open reading frame (ORF), indicating the translation of regulatory upstream ORFs (uORFs). Here, we present a workflow for the identification of translation-regulatory uORFs. Specifically, uORF-Tools identifies uORFs within a given dataset and generates a uORF annotation file. In addition, a comprehensive human uORF annotation file, based on 35 ribo-seq files, is provided, which can serve as an alternative input file for the workflow. To assess the translation-regulatory activity of the uORFs, stimulus-induced changes in the ratio of the RPFs residing in the main ORFs relative to those found in the associated uORFs are determined. The resulting output file allows for the easy identification of candidate uORFs, which have translation-inhibitory effects on their associated main ORFs. uORF-Tools is available as a free and open Snakemake workflow at https://github.com/Biochemistry1-FFM/uORF-Tools. It is easily installed and all necessary tools are provided in a version-controlled manner, which also ensures lasting usability. uORF-Tools is designed for intuitive use and requires only limited computing times and resources.

scholarly journals RNA G-quadruplexes mark repressive upstream open reading frames in human mRNAs

2017 ◽  
Author(s):  
Pierre Murat ◽  
Giovanni Marsico ◽  
Barbara Herdy ◽  
Avazeh Ghanbarian ◽  
Guillem Portella ◽  
...  
Keyword(s):  
Secondary Structures ◽  
Ribosome Profiling ◽  
Open Reading Frames ◽  
Untranslated Regions ◽  
Translation Regulation ◽  
Physical Interaction ◽  
Protein Coding ◽  
Upstream Open Reading Frames ◽  
Nucleotide Resolution ◽  
Reading Frames

ABSTRACTRNA secondary structures in the 5’ untranslated regions (UTRs) of mRNAs have been characterised as key determinants of translation initiation. However the role of non-canonical secondary structures, such as RNA G-quadruplexes (rG4s), in modulating translation of human mRNAs and the associated mechanisms remain largely unappreciated. Here we use a ribosome profiling strategy to investigate the translational landscape of human mRNAs with structured 5’ untranslated regions (5’-UTR). We found that inefficiently translated mRNAs, containing rG4-forming sequences in their 5’-UTRs, have an accumulation of ribosome footprints in their 5’-UTRs. We show that rG4-forming sequences are determinants of 5’-UTR translation, suggesting that the folding of rG4 structures thwarts the translation of protein coding sequences (CDS) by stimulating the translation of repressive upstream open reading frames (uORFs). To support our model, we demonstrate that depletion of two rG4s-specialised DEAH-box helicases, DHX36 and DHX9, shifts translation towards rG4-containing uORFs reducing the translation of selected transcripts comprising proto-oncogenes, transcription factors and epigenetic regulators. Transcriptome-wide identification of DHX9 binding sites using individual-nucleotide resolution UV crosslinking and immunoprecipitation (iCLIP) demonstrate that translation regulation is mediated through direct physical interaction between the helicase and its rG4 substrate. Our findings unveil a previously unknown role for non-canonical structures in governing 5’-UTR translation and suggest that the interaction of helicases with rG4s could be considered as a target for future therapeutic intervention.

Assessment of translational importance of mammalian mRNA sequence features based on Ribo-Seq and mRNA-Seq data

2016 ◽  
Vol 14 (02) ◽  
pp. 1641006 ◽  
Author(s):  
Oxana A. Volkova ◽  
Yury V. Kondrakhin ◽  
Ivan S. Yevshin ◽  
Tagir F. Valeev ◽  
Ruslan N. Sharipov
Keyword(s):  
Statistical Analysis ◽  
Mrna Translation ◽  
Ribosome Profiling ◽  
Translation Efficiency ◽  
Mrna Sequence ◽  
Protein Coding ◽  
Sequence Features ◽  
Additional Information ◽  
Significant Relationships ◽  
Non Coding Rnas

Ribosome profiling technology (Ribo-Seq) allowed to highlight more details of mRNA translation in cell and get additional information on importance of mRNA sequence features for this process. Application of translation inhibitors like harringtonine and cycloheximide along with mRNA-Seq technique helped to assess such important characteristic as translation efficiency. We assessed the translational importance of features of mRNA sequences with the help of statistical analysis of Ribo-Seq and mRNA-Seq data. Translationally important features known from literature as well as proposed by the authors were used in analysis. Such comparisons as protein coding versus non-coding RNAs and high- versus low-translated mRNAs were performed. We revealed a set of features that allowed to discriminate the compared categories of RNA. Significant relationships between mRNA features and efficiency of translation were also established.

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